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SOME CODES RELATED TO MY WORK (click on the title to download) |
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Determining the number of static factors in approximate factor models       Matlab Reference: L. Alessi, M. Barigozzi, M. Capasso Improved penalization for determining the number of factors in approximate static factor models Statistics and Probability Letters, 2010, 80, 1806–1813 Structural dynamic factor model for the euro area       Matlab Reference: M. Barigozzi, A. Conti, M. Luciani Do euro area countries respond asymmetrically to the common monetary policy? Oxford Bulletin of Economics and Statistics, 2014, 76, 693–714 nets     R package Reference: M. Barigozzi, C. Brownlees NETS: Network estimation for time series Journal of Applied Econometrics, 2019, 34, 347-364 Dynamic factor models and volatilties       Matlab References: M. Barigozzi, M. Hallin Generalized dynamic factor models and volatilities: recovering the market volaitility shocks Econometrics Journal, 2016, 19, C33–C60 M. Barigozzi, M. Hallin Generalized dynamic factor models and volatilities: estimation and forecasting Journal of Econometrics, 2017, 201, 307–321 M. Barigozzi, M. Hallin Generalized dynamic factor models and volatilities: consistency, rates, and prediction intervals Journal of Econometrics, 2020, 116, 4-34 Factors and networks for volatilties       Matlab Reference: M. Barigozzi, M. Hallin A network analysis of the volatility of high-dimensional financial series Journal of the Royal Statistical Society - series C, 2017, 66(3), 581–605 Non-stationary dynamic factor models       Matlab Reference: M. Barigozzi, M. Lippi, M. Luciani Large-dimensional dynamic factor models: estimation of impulse-response functions with I(1) cointegrated factors Journal of Econometrics, 2020, available online factorcpt     R package Reference: M. Barigozzi, H. Cho, P. Fryzlewicz Simultaneous multiple change–point and factor analysis for high-dimensional time series Journal of Econometrics, 2018, 206, 187-225 Factors and international financial markets       Matlab Reference: M. Barigozzi, M. Hallin, S. Soccorsi Identification of global and local shocks in international financial markets via general dynamic factor models Journal of Financial Econometrics, 2019, 17, 462-494 Locally stationary general dynamic factor model       Matlab Reference: M. Barigozzi, M. Hallin, S. Soccorsi, R. von Sachs Time-varying general dynamic factor models and the measurement of financial connectedness Journal of Econometrics, 2021, 222(1B), 324-343 Measuring output gap       Matlab Reference: M. Barigozzi, M. Luciani Measuring the output gap using large datasets The Review of Economics and Statistics, 2021, forthcoming |
OTHER CODES (click on the title to download) |
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Generalized Dynamic Factor Model       Matlab written by M. Barigozzi, M. Forni, R. Liška, M. Luciani References: M. Forni, M. Hallin, M. Lippi, L. Reichlin (2000) The Generalized Dynamic Factor Model: Identification and estimation The Review of Economics and Statistics, 82, 540-554 M. Forni, M. Hallin, M. Lippi, L. Reichlin (2005) The Generalized Dynamic Factor Model: One-sided estimation and forecasting Journal of the American Statistical Association, 100, 830-840 M. Forni, M. Hallin, M. Lippi, P. Zaffaroni (2017) Dynamic Factor Models with infinite-dimensional factor space: Asymptotic analysis Journal of Econometrics, 199, 74-92 M. Hallin, R. Liška (2007) Determining the number of factors in the General Dynamic Factor Model Journal of the American Statistical Association, 102, 603-617 |